AI agents.
Real-world
impact.

Limited visibility into sales rep performance and retailer behavior trends made it impossible to identify underperforming territories or coach reps in real time.

• Deployed Agentforce field app for real-time data collection at the point of sale
• Built AI-powered dashboards surfacing rep KPIs, visit frequency, and sell-through rates
• Configured AI agent to automatically flag low-performing retailers and trigger action plans
• Integrated leaderboard gamification module to incentivize top performers

• ✓40% improvement in sales decision-making speed
• ✓Identified and recovered 18% of previously at-risk retail accounts
• ✓Leaderboard drove 22% increase in rep-initiated retailer visits
• ✓Region managers reduced reporting time from 4 hours to 20 minutes per week

Disconnected online and in-store data meant customers received irrelevant promotions, leading to declining repeat purchase rates and low loyalty program engagement.

• Unified customer profiles across e-commerce, POS, and loyalty platforms via Data Cloud
• Agentforce agent recommends personalised offers at checkout based on purchase history
• Automated re-engagement journeys triggered by dormancy signals
• Real-time inventory-aware promotions to prevent overselling

• ✓31% increase in loyalty program active members within 90 days
• ✓Personalised campaigns outperformed generic blasts by 3.2× on conversion
• ✓Cart abandonment recovery rate improved by 27%
• ✓Customer lifetime value up 19% year-over-year

Reactive maintenance strategies were causing costly unplanned downtime, with field technicians often arriving on-site without the right parts or information.

• Integrated IoT sensor telemetry into Salesforce Asset 360 for live equipment health monitoring
• Agentforce AI agent detects anomaly patterns and raises predictive maintenance cases automatically
• Smart work order creation routes the right technician with correct parts pre-dispatched
• Knowledge base agent provides technicians with step-by-step repair guidance in the field

• ✓35% reduction in unplanned equipment downtime
• ✓Predictive alerts issued 48+ hours before failure events
• ✓First-time fix rate improved from 62% to 84%
• ✓Annual maintenance cost reduced by $1.2M across 3 plants

Dealers placed orders via email and phone calls, causing delays, errors, and zero visibility into order status — straining relationships and operational capacity.

• Launched self-service Experience Cloud portal for dealers to place, track, and modify orders
• Agentforce agent handles order queries, delivery ETAs, and return requests 24/7
• Automated credit limit checks and approval workflows for high-value orders
• Integrated ERP data to surface real-time inventory levels inside the portal

• ✓Order processing time cut from 3 days to 4 hours on average
• ✓Dealer satisfaction (CSAT) increased from 58 to 82 out of 100
• ✓60% of dealer queries now resolved without human agent involvement
• ✓Sales ops team capacity freed by 40% to focus on strategic accounts

Manual appointment reminders, fragmented care notes, and siloed patient data were resulting in high no-show rates and gaps in post-discharge follow-up care.

• Connected EHR data to Salesforce Health Cloud for a unified patient 360 view
• Agentforce agent sends personalised appointment reminders and pre-visit instructions
• Automated post-discharge outreach journeys for high-risk patients based on clinical flags
• Care coordinators receive AI-generated summaries highlighting patients needing immediate attention

• ✓No-show rate reduced by 34% within the first quarter
• ✓Post-discharge readmission rate decreased by 21%
• ✓Care coordinators handle 2× the patient caseload with AI-assisted triage
• ✓Patient satisfaction scores improved by 18 points NPS

Sales reps lacked visibility into device usage patterns and service histories, causing missed renewal opportunities and reactive service escalations.

• Integrated device telemetry and service records into Salesforce for account-level health scoring
• Agentforce renewal agent proactively alerts reps 90 days before contract expiry with suggested actions
• Automated service case creation from anomaly signals with intelligent priority routing
• Field service scheduling optimised with AI-driven territory and availability matching

• ✓Contract renewal rate improved from 71% to 89%
• ✓Service escalations reduced by 46% through proactive outreach
• ✓Average resolution time for field service cases down by 38%
• ✓Revenue from upsell at renewal increased by $2.4M annually

New wealth management client onboarding took 3–4 weeks due to manual document collection, fragmented compliance checks, and lack of advisor visibility into onboarding status.

• Built guided digital onboarding flows in Financial Services Cloud with automated document requests
• Agentforce agent follows up with clients on missing documents and answers FAQs in real time
• Compliance screening integrated with KYC/AML providers, with exceptions routed to compliance team
• Advisor dashboard shows live onboarding pipeline with bottleneck flags

• ✓Onboarding cycle reduced from 21 days to 6 days on average
• ✓Client drop-off during onboarding reduced by 43%
• ✓Compliance team effort on routine cases cut by 55%
• ✓Advisor capacity for new client acquisition increased by 30%

Loan officers relied on manual data gathering and inconsistent scoring models, while collections teams lacked prioritisation tools to focus on highest-recovery accounts.

• Agentforce agent gathers applicant data, validates documents, and pre-fills credit applications
• AI risk scoring model integrated into Salesforce to provide consistent, auditable decisions
• Collections agent segments overdue accounts by recovery probability and recommends optimal outreach
• Automated payment reminder journeys with escalation paths based on response behaviour

• ✓Loan origination time reduced by 52% end-to-end
• ✓Default prediction accuracy improved by 29% versus legacy model
• ✓Collections recovery rate on prioritised accounts up 37%
• ✓Regulatory audit preparation time reduced by 60%

Customer success teams lacked early warning signals for churn, and renewal managers were reacting to at-risk accounts too late in the cycle to course-correct.

• Built product usage health scores in Salesforce from telemetry data via Data Cloud
• Agentforce CS agent surfaces at-risk accounts with recommended intervention plays
• Automated quarterly business review (QBR) preparation with AI-generated account summaries
• Expansion opportunity agent identifies upsell triggers based on feature adoption patterns

• ✓Gross revenue retention improved from 83% to 93% within two quarters
• ✓At-risk accounts identified 60 days earlier on average
• ✓QBR prep time reduced from 3 hours to 20 minutes per account
• ✓Net revenue retention (NRR) increased by 11 percentage points

L1 support volume was growing faster than headcount, with agents spending excessive time on repetitive diagnostic tasks and knowledge lookups instead of complex problem-solving.

• Deployed Agentforce support agent to handle L1 queries with guided troubleshooting flows
• Knowledge base AI surfaces contextual articles to both customers and human agents
• Intelligent case routing escalates only unresolved issues to the right L2/L3 specialist
• Post-resolution agent triggers CSAT surveys and flags recurring issues for product teams

• ✓46% of inbound support tickets resolved autonomously without human touch
• ✓Average handle time for escalated cases reduced by 31%
• ✓CSAT increased from 72% to 88% within 6 months
• ✓Support cost per ticket reduced by 39%